NEW YORK — Researchers have generated an atlas of chromatin accessibility for individuals with varying degrees of coronary artery disease, hoping to identify mechanisms contributing to the disease.
Coronary artery disease is the leading cause of death globally, and previous genome-wide association studies have tied more than 200 genetic loci — most of which are in noncoding genomic regions — to risk for the disease. To get a better look at how genes are regulated in cells thought to be involved in CAD processes, researchers from the University of Virginia conducted single-nucleus Assay for Transposase-Accessible Chromatin (ATAC)-seq analyses in samples from people with coronary artery disease.
As they reported in Nature Genetics on Thursday, the researchers mapped about 320,000 accessible sites and found that about half the cis-regulatory elements were limited to one or just a handful of cell types, such as smooth muscle cells.
"Given that the vast majority of genetic variation associated with coronary artery disease risk resides in the noncoding genome, we wanted to interrogate the potential function of these noncoding variants using a scalable and high-resolution method at the single-cell/single-nucleus level. Also, we knew this method would work on frozen, archived tissue samples, so that would allow us to gain insights into disease risk at various stages," senior author Clint Miller from UVA said in an email.
The researchers profiled the accessible chromatin within more than 28,000 nuclei isolated from coronary artery samples from 41 patients with varying levels of coronary artery disease. Through this, they identified 14 clusters that largely represented different cell types, such as smooth muscle cells, endothelial cells, fibroblasts, T cells, and natural killer cells.
This atlas could help researchers tease out what cells or cell types contribute to disease risk, they noted, as well as help home in on candidate causal genes and variants.
Through additional regulatory profile analyses, they uncovered a number of cell-type-specific elements and transcription factors. For instance, certain transcription factor motifs were more common in particular cells: ETS and SOX family motifs occurred more often in endothelial cells, while RUNX family motifs were more frequent in T cells.
They likewise found that genetic loci linked to coronary artery disease in previous genome-wide association studies were also enriched in particular cell types. Coronary artery disease and blood pressure-associated variants were enriched in smooth muscle cells, endothelial cells, and macrophages, while pulse pressure-linked variants were specific to smooth muscle cells.
Meanwhile, the researchers folded in chromatin accessibility quantitative trait locus (caQTL) data to prioritize candidate functional GWAS variants. In particular, they noted a caQTL at the MRAS locus that affects an MEF2 binding site in smooth muscle cells. MRAS, they pointed out, has a role in Noonan syndrome-associated cardiomyocyte hypertrophy, suggesting that this finding could provide insight into smooth muscle cell growth responses in coronary artery disease.
Further, by combining their scRNA-seq data with co-accessibility information, the researchers began to identify transcriptional regulators that could influence disease risk through their effect on downstream gene regulatory networks. They in particular homed in on the transcription factor genes PRDM16 and TBX2, which likely affect such networks in smooth muscle cells. PRDM16 is thought, they noted, to be involved in the perivascular bed and the regulation of blood flow. TBX2, meanwhile, is known to have a role in the atrioventricular development of the heart as well as roles in brain and limb development and in cancer.
Additional functional studies, the researchers noted, could uncover further disease risk mechanisms.
"The next step is to perform more systematic validation of these candidate regulatory elements to prioritize functional enhancers in both normal and disease-relevant contexts," Miller added. "It will be important to apply genome editing approaches to elucidate causal roles for regulatory elements and variants in specific cell types. Functional assays will be critical to determine how these epigenomic changes affect downstream processes and inform new druggable targets or biomarkers."